From One Countable Win to a System That Scales Itself
The wisdom of starting small and getting your bearings
On a call this morning, an engineering leader told me about his company’s AI showcase.
The idea was lovely. Once a week, anyone doing something interesting with AI would demo it to the group, trumpet the win, and inspire the next person to go try something of their own. It would fill the pipeline with ideas and let the best ones rise, a little like a startup competition. Everyone was behind it. And it has met exactly once, because on the day they gathered there was only one thing to demo. Now it gets quietly canceled most weeks.
Most organizations I chat intuitively move in the right directions. They start small. They run pilots. They name champions. They fire up slack channels. Then they wait for it to spread on its own. It rarely does.
That’s because there is another layer needed. A layer to catch the win and turns it into the next one. That layer is mostly human, and it is missing from most AI implementations.
First Look for AI Impact, Not Scale
I have a saying that shopping is the easy part. Meaning, it is easy to buy AI licenses… or a platform to track token usage. But shopping for licenses won’t teach a person to use AI, nor will it teach a programmer how to get more out of the model for fewer tokens. No more than buying tile gets you a new shower. You still have the same problem: implementation is the hard part.
Here is the pattern I’d rather see.
Somewhere in that company are two or three people who already have their token usage dialed in, who get excellent results without burning the budget. Find them. Make them your first AI leads. Not champions, leads.
People who lead through influence rather than authority. People who know how to transfer knowledge. People who have a remit to show their peers how they get great results. Now you have something you can count. You started with three efficient users, you activated them to teach, and a month later you can point to the number that moved and the dollars that came back.
That countable result is the seed. It is small on purpose, because a small, measurable win is the only thing that reliably frees up the budget and the patience for the next, larger one.
When your team lands its next win with AI, who is responsible for catching it and getting it in front of the next person? If the answer is ‘no one,’ you have found your gap.
Build the Pockets that Ripple AI Out
Another leader I spoke with last week runs global development inside a professional-services firm of roughly a quarter-million people across a hundred and fifty-plus member firms. She is a systems thinker, and she has arrived, on her own, at something I wish more leaders understood in their bones. She told me you cannot do anything at the global level if you have not built your pockets first, because those pockets go on to activate everyone else.
The spreading is what needs infrastructure. A network of AI Activation Hubs are where the win gets caught. A hub keeps current on what the tools can do, atomizes that into something a busy person can actually use, tracks where AI is creating value, and codifies the good patterns so the automation someone built in one corner can show up in another. Without it, every win stays local, and you are back to demos that stay local.
You Have the People You Need; They Just Have Different Titles
Underneath everything I’ve described, the AI Leads and the Activation Hubs, is a suggestion that your organization needs some roles it does not have yet. That can feel radical, and I understand why. Most leaders I talk with already feel fully staffed. They look at the org chart, see capable people in every seat, and, if anything, feel pressured to shrink headcount. So why would this be the moment to talk about new work and new roles?
Because this is exactly how jobs change. A job is a bundle of tasks and decisions and handoffs, and when a technology this big arrives, that bundle gets taken apart and put back together in a new shape. Some of that new shape is the connective work I keep pointing at, the people who help their peers get results and the hubs that catch what those people learn. It is not more headcount stacked on top of the old structure. It is a few of your existing people picking up genuinely new work, because the old bundle no longer fits.
Which is why you start small. We have watched big-bang transformations disappoint for thirty years, from the ERP rollouts to the digital reinventions that reorganized everything at once and delivered very little. Radical reinvention rarely survives a simple declaration from the top. They have to earn their place in your context, in front of people who can see the result. You start small, you get the win you can count, you show that a lightly-appointed AI Lead and a small hub actually moved something, and then you have the standing to build on it.
So, Where Do You Find Your Meaningful Wins?
Look in three places.
First, find a problem the business already cares about and can measure, the way my engineer has runaway token costs staring him in the face. A win only counts if someone was already keeping score.
Second, find the people quietly getting great results without being told to, because those are sometiems your AI Leads before they have the title, and they are usually easy to spot once you ask.
Third, find the pocket with appetite, the team leaning in rather than the one you would have to drag, so your first win arrives with pull instead of push.
None of this requires a reorganization or a grand announcement. It takes a countable win and some small piece of human infrastructure to catch the win and spur on ,the next one. That is how a change this large earns its right to spread. It is how you get, one proven pocket at a time, to become AI-native.
If this is the kind of thinking you want more of, consider reading the book Hyperadaptive: Rewiring the Enterprise to Become AI-Native or joining a Running Hyeperadaptive Organizations cohort.